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Cross-section without factors: a string model for expected returns.
Quant Finance
June 2024
Frankfurt School of Finance & Management, Adickesallee 32-34, Frankfurt, Germany.
Many asset pricing models assume that expected returns are driven by common factors. We formulate a model where returns are driven by a string, and no-arbitrage restricts each expected return to capture the asset's granular exposure to all other asset returns: a correlation premium. The model predicts fresh properties for big stocks, which display higher connectivity in bad times, but also work as correlation hedges: they contribute to a negative fraction of the correlation premium, and portfolios that are more exposed to them command a lower premium.
View Article and Find Full Text PDFLeveraging mobility data to analyze persistent SARS-CoV-2 mutations and inform targeted genomic surveillance.
Elife
January 2025
Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
Given the rapid cross-country spread of SARS-CoV-2 and the resulting difficulty in tracking lineage spread, we investigated the potential of combining mobile service data and fine-granular metadata (such as postal codes and genomic data) to advance integrated genomic surveillance of the pandemic in the federal state of Thuringia, Germany. We sequenced over 6500 SARS-CoV-2 Alpha genomes (B.1.
View Article and Find Full Text PDFFunctional resting state connectivity is differentially associated with IL-6 and TNF-α in depression and in healthy controls.
Sci Rep
January 2025
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159, Mannheim, Germany.
Inflammatory processes have been implicated in the pathophysiology of depression. In human studies, inflammation has been shown to act as a critical disease modifier, promoting susceptibility to depression and modulating specific endophenotypes of depression. However, there is scant documentation of how inflammatory processes are associated with neural activity in patients with depression.
View Article and Find Full Text PDFApplication of Large Language Models in Medical Training Evaluation-Using ChatGPT as a Standardized Patient: Multimetric Assessment.
J Med Internet Res
January 2025
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Background: With the increasing interest in the application of large language models (LLMs) in the medical field, the feasibility of its potential use as a standardized patient in medical assessment is rarely evaluated. Specifically, we delved into the potential of using ChatGPT, a representative LLM, in transforming medical education by serving as a cost-effective alternative to standardized patients, specifically for history-taking tasks.
Objective: The study aims to explore ChatGPT's viability and performance as a standardized patient, using prompt engineering to refine its accuracy and use in medical assessments.
Concurrent symptom domains and associations with recovery timelines among collegiate athletes with sport-related concussion.
Br J Sports Med
December 2024
Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA.
Objective: Concussion symptoms can be clustered into domains and understanding how multiple symptom domains present clinically may guide more accurate interventions. We investigate the associations between concurrent symptom domains and clinical recovery outcomes, as well as the role of sex in these relationships.
Methods: We analysed data from the Ivy League-Big Ten Epidemiology of Concussion Study and included sport-related concussions (SRC) across five academic years 2015-2016/2019-2020 with complete data (n=1160).
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